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TheTempAccount avatar TheTempAccount commented on July 21, 2024

脸部的68个关键点的定义应该是通用的,可以查一下,把多余的点去掉。我用的是https://github.com/MVIG-SJTU/AlphaPose.git检测的,把结果转成了OpenPose的格式。

模型里只使用了12个点,输出文件里多余的点是无效的,主要是为了和OpenPose的格式一致。训练Vid2Vid的时候也没有画这些无效的点。

from co-speech-motion-generation.

Olivia-Ye avatar Olivia-Ye commented on July 21, 2024

脸部的68个关键点的定义应该是通用的,可以查一下,把多余的点去掉。我用的是https://github.com/MVIG-SJTU/AlphaPose.git检测的,把结果转成了OpenPose的格式。

模型里只使用了12个点,输出文件里多余的点是无效的,主要是为了和OpenPose的格式一致。训练Vid2Vid的时候也没有画这些无效的点。

谢谢您的回复!!!
请问能否分享一下训练vid2vid的过程呢?我在尝试剔除openpose中无效的点之后,只剩下pose的12个点,face68个点,单核训练了30轮的效果并不好,从模型保存的每一轮的flow光流图像和conf图像上看,也不能达到网上的效果,请问您有没有遇到类似的情况呢?此外我也有一种猜想,是不是需要输入训练和测试的img是高分辨率呢?
flow光流图像
epoch007_flow_ref

conf图像
epoch007_conf_ref

我在网上看到的训练10epoch的效果
20190416195413918

from co-speech-motion-generation.

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